This K24 award will enable the investigator to launch a transdisciplinary mentorship program for mHealth research focused on obesity and cardiovascular disease (CVD) prevention. The candidate currently has 15 mentees including 7 post-doctoral fellows/junior faculty and 8 graduate students. Altogether she has co- authored 119 papers with mentees and they have obtained 17 grants under her mentorship. The proposed mentorship plan will formalize and intensify her mentorship activity by providing mentees with a transdisciplinary mentoring experience that represents experts in behavioral science, preventive cardiology, health informatics, health economics, computer science, and engineering. Mentees from collaborating labs at the UMass Medical School, UMass Amherst, and Worcester Polytechnic Institute will embed in each other's lab to learn a broad range of mHealth and clinical research skills. Mentees will learn how to: utilize mobile apps and online social networks in their research; analyze online social network data; conduct qualitative data analyses; conduct usability testing; employ behavior change strategies in mobile and social network environments; design preliminary studies; and write grants. The candidate's midcareer training goals are to enhance knowledge and skills in mobile technology and social network analyses, establish a transdisciplinary mentorship program in mHealth research targeting CVD risk reduction, assist mentees to become independent investigators, and ultimately, to contribute to the scientific workforce focused on mHealth solutions for CVD prevention. The overarching goal of the research plan is to test ways to leverage mobile technologies and online social networks to increase the impact, scalability, cost-effectiveness, and dissemination potential of behavioral interventions. Three research aims are proposed, all of which examine the feasibility of novel technology-driven ways to deliver behavior change strategies. The first aim proposes to develop and test the proof-of-concept of a mobile app that will use sensing technology to identify physiological and environmental triggers for overeating. Findings will inform an app designed to identify key moments users would benefit from behavioral support. The second aim is to develop and test the proof-of-concept of a weight loss mobile app that contains an avatar-facilitated, idiographic problem solving feature that processes information intelligently to help patients identify solutions to their weight loss problems. The third aim is t test the feasibility of a lifestyle intervention that is delivered via an online social network. Al of the proposed interventions were designed to minimize or eliminate patient visits. This work will provide preliminary data for 3 trials testing the efficacy of these interventions in patient care settings. Identifying cost-effective and scalable means to treat obesity is a public health priorit given the spiraling healthcare costs associated with obesity. The proposed work will produce data toward that end and contribute to the mentorship of the next generation of researchers who will have transdisciplinary expertise to capitalize on mobile technologies in the prevention of CVD.